Monday, March 16, 2015

The old adage, "Work Smarter, Not Harder!" has become a staple in the way people go about work of any kind.

My advice: "Work Smart AND Hard!".

The problem with the options "working hard" and "working smart" is that all too often we think we can choose "hard or "smart".

The question is, why aren't we doing both?

Both should be approached as a way to find success because both are essential, and it's time to stop treating them as if they were mutually exclusive.

Working excessively long hours? This may not be helpful because 6 hours , when the work is efficient, can be just as productive as an 8 hours and objectives will be achieved. Working hard? This is different! You do not come across success just by hoping for it! To achieve true success, you need work hard to reach your fullest potential.

Hard-working people are not workaholics!

Many people confuse hard-working people with workaholics.

Workaholism means that someone value work over any other activity, even when it negatively affects him. On the other hand, there are many people who work hard, but still enjoy others activities when they have free time.

How to Work Smarter? There are a few key things that can help people to do this:

- Understand your strengths and weaknesses - this is my golden rule.

- Make the best of resources available - I learned (the hard way) that always you must explore "what’s right there" in front of you.

- Prioritize: This is very important in time management. Each day, identify the tasks that are the most crucial to complete, and do those first. Devote your entire focus to the task at hand. Pay attention to details.

Monday, January 12, 2015

A couple of months ago, Google started rolling out its new Android 5.0 Lollipop operating system and one of the most prominent changes in the Lollipop release is a redesigned user interface built around the “Material design”.

Here’s Google’s definition of Material design: “a visual language for users that synthesizes the classic principles of good design with the innovation and possibility of technology and science”.Google has left behind the world of skeuomorphic design and the result is something that looks more eye-catching.

Saturday, January 10, 2015

Statistical Analysis and Data Mining? Middleware and Integration Software?
There are good times for you if you have these skills!

"Statistical analysis and data
mining" topped LinkedIn's list of the 25 Hottest Skills That Got
People Hired in 2014, moving up from number 5 in 2013.

"We live in an increasingly data driven world, and businesses are
aggressively hiring experts in data storage, retrieval, and analysis.
Across the globe, statistics and data analysis skills were highly
valued" Sohan Murthy, research
consultant at LinkedIn, wrote in a blog post.

Glassdoor reports a median salary of $118,709 for a data scientist
and $64,537 for a programmer.

If you have any involvement in data analytics and want to develop your
career, is worth learning some of the most commonly used tools:

- SQL/RDB;

- R and Python;

- Excel;

- SAS and SPSS;

-Hadoop.

There are lots of roles that involve working with analytics and big data,
but some of the most common titles are:

- Data Analyst - Common skills that you will be asked for include
SQL, R, SAS and Excel, and often Hadoop.

- Data Scientist - As well as the analytics skills that an analyst
will be expected to have, data scientists will be expected to have programming
skills (Java or Python).

In 2014, for the second year, O'Reilly Media conducted an anonymous survey
to expose the tools successful data analysts and engineers use, and how those
tool choices might relate to their salary.

By a considerable margin, the most broadly-used software was SQL , which
was selected by 71% of respondents.

R and Python were the next most widely-used tools — they were selected by
43% and 41% of survey-takers, respectively.

"R and Python are likely popular because they are easily accessible
and effective open source tools for analysis",the authors of the report
note.

Moreover, statistics has been working on collecting and analyzing data even
before computers existed. Whatever technological revolutions that may occur,
statistics will remain relevant because if we can measure something, we improve
it.

Related skills were also ranked highly:

6. Business Intelligence

10. Perl/Python/Ruby

11. Data Engineering and Data Warehousing

The rest of the LinkedIn's list was populated by tech skills.

Hottest Skills of 2014 on LinkedIn:

1. Statistical analysis and data mining

2. Middleware and integration software

3. Storage systems and management

4. Network and information security

5. SEO/SEM Marketing

6. Business intelligence

7. Mobile development

8. Web architecture and development framework

9. Algorithm design

10. Perl/Python/Ruby

Last year, the top 2013 LinkedIn skill was Social Media Marketing, with
Statistical Analysis and Data Mining ranked at 5.